Multiresolution Spatiotemporal Data Structure for E&P Subsurface Data Storage and Analysis
Duncan H. B. Irving, N. O‘Doherty, Mansoor Ahmad Rasheed · Proceedings · 2011
We draw upon insights gained from working with integrated massive (petabyte scale) and time-sensitive datasets in other industries. We describe the development of a Spatiotemporally-Registered Data Structure (SRDS) that allows multiresolution spatial and temporal data types from subsurface and production/operation domains to coexist in the same data structure and how this data structure can be exposed as various industry-standard logical data models. We compare our data structure to current GIS-, database- and application-centric data structures and demonstrate data management and data interactivtity improvements against each paradigm. The SRDS permits and promotes efficient storage and interaction with structured and unstructured multi-resolution datasets at the Petabyte scale; and, on the appropriate architecture, enhances realtime analytical capabilities. The SRDS is built on Massively Parallel Processing (MPP) database architecture implemented by a Teradata® RDBMS that is compliant with the ANSI SQL 2008 standard. We demonstrate how this architecture is the most appropriate for this task and show how such a platform can play a part in a broader enterprise data management landscape.